Friday, March 1, 2024

ECMWF AI Forecasts

The weather industry has been abuzz with excitement in the past year about the new AI (Artificial Intelligence) forecast models; I penned a few comments back in November:

The latest news is that ECMWF is now providing the realtime forecast data from its AIFS model, and it's open and free for all to use.  You can see the 4 forecasts per day on Levi Cowan's website:

The skill of the model is comparable to the leading physics-based models, so the new data will provide a useful tool for forecasters.  I'll be keeping an eye on it for Alaska.

We should bear in mind, however, that ECMWF currently runs only a single AIFS forecast each time, rather than an ensemble of forecasts like the ECMWF, NOAA, and Canadian ensemble systems.  Ensemble forecasts provide valuable information on confidence ("how similar are the ensemble members?"), and the ensemble-average forecasts tend to be more stable from run to run.  The AIFS forecasts will have a tendency to jump around from run to run, so take each iteration with a pinch of salt.

For example, here are the 4 latest AIFS forecasts for the morning of March 11, i.e. 10 days ahead, and probably at or beyond the limit of deterministic predictability for the Alaska region.  From oldest to newest forecasts:

The general theme is the same - cold in northern Alaska - but the individual forecasts disagree on the extent of cold farther south.

For comparison, here's the NOAA GEFS ensemble mean for the same time.  In this case the overall agreement is pretty good; and these forecasts (GEFS vs AIFS) are produced by completely different methods.  Impressive technology for sure!


  1. Thanks for the AI update Richard. Looks like mid-March before we'll see Spring's warmth. Moving NW from Canada some warm air appears to advect in most models, incl AI.

  2. Interested in your analysis of the long duration north wind event at ANC

    1. Thanks for asking, it will be interesting to take a look. The duration of well over 72 hours does seem significantly unusual for the location.